Data from: Exploring the macroevolutionary impact of ecosystem engineers using an individual-based eco-evolutionary simulation
Data files
Mar 29, 2024 version files 754.89 MB
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README.md
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Smith_et_al_2024_SI.zip
Abstract
Ecosystem engineers can radically reshape ecosystems by modulating the availability of resources to other organisms through modifying either physical or biological aspects of the environment. The introduction or removal of ecosystem engineers from otherwise stable ecosystems can impact the diversity of co-occurring species, such as driving local extinctions of native taxa. While these impacts are well established over ecological timescales for a wealth of taxa, the macroevolutionary implications of the onset of ecosystem engineering behaviours are less clear. Despite this uncertainty, ecosystem engineering has been implicated in several major transitions in Earth's history including the appearance of extensive bioturbation during the Cambrian substrate revolution and associated Ediacaran-Cambrian turnover and the Great Oxygenation Event. Whether ecosystem engineers are frequently associated with turnover and extinction in deep time is not known. Here we investigate this with an eco-evolutionary simulation framework in which we assign lineages the ability to impact the fitness of co-occurring taxa through phenotype-environment feedback. We explore numerous conditions, including how frequently these feedbacks occur, and whether ecosystem engineers modify or create niches. We show that there is no general expected outcome from the introduction of ecosystem engineers. In a minority of runs, ecosystem engineering lineages completely dominate, rendering all others extinct, but in others, they persist (but do not dominate), or die out. We suggest that ecosystem engineers have complex impacts but possess the capacity to profoundly shape diversity, and it is appropriate to consider them alongside other exogenous extinction drivers in deep time.
README: Data from: Exploring the macroevolutionary impact of ecosystem engineers using an individual-based eco-evolutionary simulation
https://doi.org/10.5061/dryad.9zw3r22p7
This folder contains the supplementary information for the paper Exploring the macroevolutionary impact of ecosystem engineers using an individual-based eco-evolutionary simulation
In the root directory, there is a bash script called Run_pipeline.sh - running this will extract the data to your machine, and then run the required R analyses before outputting the figures for you in the root directory. It may be necessary to provide these execute permissions (i.e. run chmod +x ./Run_pipeline.sh in the root directory).
Subfolder "Simulation_data"
Inside the subfolder "Simulation_data", there are five compressed folders: (1) Baseline_runs.zip, (2) EE_once_add_mask.zip, (3) EE_once_overwrite_mask.zip, (4) EE_persistent_add_mask.zip, and (5) EE_persistent_overwrite_mask.zip
These folders contain the raw data generated by TREvoSim 3.0.0 (1) in the absence of ecosystem engineering, (2) when a mask is added at the halfway point but otherwise left unaltered, (3) when a mask is added at the halfway point and overwritten every 500 generations, (4) when a mask is overwritten at the halfway point, and (5) when a mask is overwritten at the halfway point and overwritten every 500 generations respectively.
If being run manually (i.e. not using the shell script), these should be extracted to identically named folders within Simulation_data
Subfolder "Analytical_pipeline"
Inside subfolder "Analytical_pipeline", there three R scripts. If the analysis is manual (i.e. not using the shell script), these should be run in the following order: (1) data_processing_and_analysis.R, (2) plotting_figure_3.R, and (3) rate_calculation_and_plotting.R
data_processing_and_analysis.R generates lineage through time data from the raw TREvoSim outputs for all EEs and a randomly selected non-EE, calculates the proportion of replicates in which these lineages survive and dominate for each simulation, and collates the final species richness of each replicate.
plotting_figure_3.R plots the proportion of replicates in which randomly selected non-EE and EE lineages survive until the end of the simulation, dominate the simulation, and go extinct.
rate_calculation_and_plotting.R calculates the per-iteration, per-lineage extinction and speciation rates for each simulation and plots them.